
During September 2025, Wangyue developed the BatonVoice subsystem for the Tencent/digitalhuman repository, establishing a modular core architecture for multi-mode text-to-speech. Leveraging Python and Gradio, Wangyue built a unified interface that integrates a TTS engine, audio feature extractor, and a Gradio-based UI, enabling fine-grained control across multiple TTS modes. The work included integrating external TTS dependencies via Git submodules, streamlining build and maintenance processes. Wangyue also overhauled documentation and media assets to improve onboarding and cross-team collaboration. By simplifying prosodic feature output in the Gemini client, Wangyue enhanced result readability and downstream processing, strengthening maintainability and production readiness.

In September 2025, the Tencent/digitalhuman BatonVoice work established a solid foundation for multi-mode TTS with a scalable architecture and improved developer experience. Key platform improvements include a modular BatonVoice core architecture with a Gradio-based multi-mode UI, integrated external TTS dependencies via submodules, and a comprehensive documentation/media assets refresh that aligns resources for onboarding and cross-team usage. A simplification of prosodic feature output in the Gemini client further enhances readability and downstream processing. These efforts collectively reduce time-to-value for new TTS experiments, improve build stability, and strengthen long-term maintainability across the BatonVoice subsystem.
In September 2025, the Tencent/digitalhuman BatonVoice work established a solid foundation for multi-mode TTS with a scalable architecture and improved developer experience. Key platform improvements include a modular BatonVoice core architecture with a Gradio-based multi-mode UI, integrated external TTS dependencies via submodules, and a comprehensive documentation/media assets refresh that aligns resources for onboarding and cross-team usage. A simplification of prosodic feature output in the Gemini client further enhances readability and downstream processing. These efforts collectively reduce time-to-value for new TTS experiments, improve build stability, and strengthen long-term maintainability across the BatonVoice subsystem.
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